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Monitoring land use change of Meyjaran Dam area before and after construction using remote sensing and GIS techniques

Document Type : Research Paper

Authors

  • Mojtaba Golbaf 1

  • Farbod Papoli Yazdi 2

  • Fereshteh Modaresi 2

  1. 1 Department of Remote Sensing, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
  2. 2 Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
DOI icon https://doi.org/10.22034/ewe.2025.494716.1992

Abstract

The construction of large dams in regions with temperate climates and dense forest cover causes significant land use changes that require precise assessment and continuous monitoring. To prevent the worsening of crises related to vegetation degradation and the loss of natural resources, the cumulative impacts of dam construction must be evaluated over time using a hydro-ecological approach. This study investigates land use and vegetation cover changes in the Meyjaran Dam basin over 30 years. Satellite imagery from Landsat 5 and Sentinel-2B was employed to assess the pre- and post-construction periods. Land use changes were analyzed in two spatial extents: a small study area (464 ha) and a larger watershed (4,027 ha) that includes the study area and the upstream dense forest cover. Image classification was performed using supervised classification with the Maximum Likelihood algorithm, achieving a Kappa coefficient of 0.99. Spatial change analysis was conducted using the Location Quotient (LQ) index. The results indicated that within the small study area, forest cover declined by 84.22 ha (18.14%), while built-up areas increased by 25.25 ha, and rangelands and agricultural lands grew by 24.19 ha. In the larger watershed, forest cover decreased by 120.80 ha (3%). These findings highlight the extensive ecological impacts of dam construction on forest ecosystems beyond the immediate inundation zone.

Keywords

Subjects

 environment

References
Alavi Panah, M. (2003). Remote Sensing and Geographic Information System. University of Tehran Press, Tehran. 311 p. [In Persian].
Almalki, R., Khaki, M., Saco, P. M., & Rodriguez, J. F. (2023). The impact of dam construction on downstream vegetation areas in dry areas using satellite remote sensing: A case study. Remote Sening, 15(21), 5252. https://doi.org/10.3390/rs15215252
Asghari, S., Jalilyan, R., Pirozineghad, N., Madadi, A., & Yadeghari M. (2020) Evaluation of water extraction indices using landsat satellite images (Case study: Gamasiab River of Kermanshah). Journal of Applied Research in Geographical Sciences, 20(58), 53-70. doi:10.29252/jgs.20.58.53 [In Persian].
Baluchi, B., Dehghani, M., & Nikoo, M. R. (2016). Assessing land-use change induced by the Karkhe Dam using satellite images and maximum likelihood classification method. Scientific Quarterly of Water Resources Engineering, 9(28), 19-32. 20.1001.1.20086377.1395.9.28.2.3  [In Persian]
Beleites, C., Neugebauer, U., Bocklitz, T., Krafft, C., & Popp, J. (2013). Sample size planning for classification models. Analytica Chemical Acta, 760, 25–33. https://doi.org/10.1016/j.aca.2012.11.007
Castro-Diaz, L., Lopez, M. C., Moore, S., Radonic, L., Hodbod, J., & Moran, E. (2024). Multidimensional and multitemporal energy injustices: Exploring the downstream impacts of the Belo Monte hydropower dam in the Amazon. Energy Research and Social Science, 113, 103568. DOI:https://doi.org/10.1016/j.erss.2024.103568
Darikandeh, D., Ghorbani, D., & Shahnazari, A. (2020). Monitoring changes caused by the construction of the alborz dam on land cover and land use through remote sensing and geographic information systems. Journal of Watershed Management Research, 11(21), 24-35. DOI:10.52547/jwmr.11.21.24
Kamali, M., & Didari, S. (2024). Investigating the effects of constructing the Mulla Sadra Dam and land use changes on water resources in downstream basins. Proceedings of the First National Conference on the Future and Sustainability of the Environment, Tehran. https://civilica.com/doc/2112502  [In Persian]
Linh, H. T., Truc, D. T., Binh, N. T., & Tri, V. P. D. (2025). Assessing water governance trends and challenges at a local level—an application of the OECD water governance framework in Soc Trang Province, Vietnam. Water, 17(3), 320. https://doi.org/10.3390/w17030320
Motkan, A.A., Saeedi, K.H, Shakiba, A. & Hoseini Asl, A. (2010). Evaluation of land cover changes in relation to Taleghan Dam using remote sensing techniques. Journal of Applied Geosciences Research, 16(19): 45-64, http://jgs.khu.ac.ir/article-1-610-fa.html [In Persian].
Namdar, F., Mahmoudi, S., Esmali Ouri, A., & Pazira, E. (2021). Monitoring of Thirty Years of Land Cover Changes Using Remote Sensing and GIS (Case Study: Qaresu Watershed, Ardabil). Journal of Environmental Science and Technology, 22(12), 179-190. Doi: 10.22034/jest.2020.45905.4755  [In Persian].
Ouma, Y. O., Nkwae, B., Odirile, P., Moalafhi, D. B., Anderson, G., Parida, B., & Qi, J. (2024). Land-use change prediction in dam catchment using logistic regression-CA, ANN-CA, and random forest regression and implications for sustainable land–water nexus. Sustainability, 16(4), 1699. https://doi.org/10.3390/su16041699
Richards, J. A. (2022). Supervised classification techniques. In:  Remote sensing digital image analysis, Springer, Cham. 263-367. https://doi.org/10.1007/978-3-030-82327-6_8
Sanjari, S., & Boroomand, N. (2013). Land Use/Cover Change Detection in Last Three Decades Using Remote Sensing Technique (Case Study: Zarand Region, Kerman Province). Journal of RS GIS for Natural Resources, 4(1), 57-67. https://sid.ir/paper/189604/fa [In Persian].
Sengupta, D., Klein, S., Raine, J. A., & Golling, T. (2024). CURTAINs flows for flows: Constructing unobserved regions with maximum likelihood estimation. SciPost Physics, 17(2), 046. https://doi.org/10.21468/SciPostPhys.17.2.046
Senseman, G. M., Bagley, C. F., & Tweddale, S. A. (1996). Correlation of rangeland cover measures to satellite‐imagery‐derived vegetation indices. Geocarto International, 11(3), 29–38. https://doi.org/10.1080/10106049609354546
Shahiki Taash, M. N., & Roodini, K. (2019). Measuring the geographical concentration factor of factory industries and the importance of industrial specialization in the provinces of Iran. Geography and Regional Urban Planning, 9(31), 173–196. https://doi.org/10.22111/gaij.2019.4711
Thakkar, A. K., Desai, V. R., Patel, A., & Potdar, M. B. (2017). Impact assessment of watershed management programs on land use/land cover dynamics using remote sensing and GIS. Remote Sensing Applications: Society and Environment, 5, 1-15. https://doi.org/10.1016/j.rsase.2016.12.001
U.S. Geological Survey. (1991, August 28). Landsat 5 TM image, Path 165, Row 35 [Satellite image]. USGS EarthExplorer. https://earthexplorer.usgs.gov
U.S. Geological Survey. (2021, September 2). Sentinel-2B MSI image, Tile T39V [Satellite image]. USGS EarthExplorer. https://earthexplorer.usgs.gov
Yu, H., Zahidi, I., Fai, C. M., Liang, D., & Madsen, D. Ø. (2025). Tailings dam failures: A critical evaluation of current policies and practices. Results in Engineering, 25, 103973. https://doi.org/10.1016/j.rineng.2025.103973
Zarei, H., Shanani Hoveyzeh, S. M., & Joorabian Shooshtari, S. (2024). Temporal-Spatial Prediction of Land Use Changes Using LCM Model in Doroodzan Dam Watershed. Environment and Water Engineering, 10(3), 363-378. https://doi.org/10.22034/ewe.2023.408348.1881  [In Persian].
Environment and Water Engineering

Volume 11, Issue 2
March 2025

Pages 155 - 164

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  • Receive Date: 08 April 2025
  • Revise Date:
  • Accept Date: 08 April 2025
  • Publish Date: 08 April 2025
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